Adds regression tests for #2020

[geoffreyangus]

Adds regression tests for #2020, a PR that implemented a fix for NaNs introduced via an outer join concat in the dask df engine.

While writing these tests, I found that PandasEngine.df_like was also doing an outer join of proc_cols (implicitly through pd.DataFrame init) instead of an inner join, similarly leading to NaN values in columns whose preprocessing step called for dropping rows (typically OutputFeature features). This is remedied through an inner join concat. We would like to be able to implement an inner join concat in the dask df engine in the future. It is not currently possible in the dask df engine due to the parallel nature of dask dataframes.

[github-actions]

Unit Test Results

       6 files  ±0         6 suites  ±0   1h 43m 28s ⏱️ + 11m 49s
2 774 tests ±0  2 741 ✔️ +1    33 💤 ±0  0 ❌  - 1 
8 322 runs  ±0  8 219 ✔️ +1  103 💤 ±0  0 ❌  - 1 

Results for commit 6c98b34. ± Comparison against base commit 2c3fe2e.

♻️ This comment has been updated with latest results.

[geoffreyangus]

This function converts nan_percent of samples in each row of the CSV into NaN. This is important for tests that drop rows for exactly one feature– with this change, one has guarantees about the number of rows that will be dropped.

Example:
In a unit test, we are simulating predicting the targets column which is missing 10% of samples. We choose to drop rows missing a value for targets. With this sampling scheme, we know we will have exactly 90% of samples left.